• ETRI Journal
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• v.43 no.5
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• pp.835-855
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• 2021

With the recent increase in data disclosure, the Comprehensive Knowledge Archive Network (CKAN), which is an open-source data distribution platform, is drawing much attention. CKAN is used together with additional extensions, such as Datastore and Datapusher for data management and Harvest and DCAT for data collection. This study derives the problems of CKAN itself and Harvest Extension. First, CKAN causes two problems of data inconsistency and storage space waste for data deletion. Second, Harvest Extension causes three additional problems, namely source deletion that deletes only sources without deleting data themselves, job stop that cannot delete job during data collection, and service interruption that cannot provide service, even if data exist. Based on these observations, we propose herein an improved CKAN that provides a new deletion function solving data inconsistency and storage space waste problems. In addition, we present an improved Harvest Extension solving three problems of the legacy Harvest Extension. We verify the correctness and the usefulness of the improved CKAN and Harvest Extension functions through actual implementation and extensive experiments.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.59-65
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• 2018

As open data(public data) began to be recognized as a source of national economic development, many countries began to build public data portals and provide open data to the private sector. In accordance with this trend, open source communities have begun to develop open data platform such as CKAN and enable to share dataset among open data platforms by applying metadata standard technology. However, many governments and local governments are still making it difficult to share data between data portals because they build their own platforms. In this paper, we propose a DCAT-based metadata transformation tool to solve these problems, and show how to transform a dataset into DCAT.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.2
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• pp.149-178
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• 2013

Recently many countries have established data platforms to disclose government-owned data that include administrative data-sets and provide free access to the public via Web. This research analyzes the "Socrata" and "CKAN", the most popular representative open data platforms in the world, and reviews functions and their practical cases in operation in several cities of various nations. It also examines the current status of the data-set services in the City of Seoul to provide conceptual bases for management and service of the local governments' data-sets using open data platform. Then it suggests measures that ensure the long-term preservation and management of data-sets as archives for services, which includes the aspects of preparing systems, creating and managing data, providing services, and selecting platforms.

• Korea Information Processing Society Review
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• v.23 no.5
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• pp.53-63
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• 2016

국/내외의 공공 데이터 공유 개방 흐름에 힘입어, 데이터기반의 다양한 비즈니스 기회가 창출되면서, 데이터를 효과적으로 공유 관리하기 위한 오픈 데이터플랫폼이 공공, 과학기술 분야를 중심으로 확산 발전하고 있다. 공공분야에서는 공공데이터 공유를 위한 CKAN, Socrata 등의 플랫폼이 있으며, 연구분야에서는 DSpace를 기관 데이터 공유 레파지토리(repositories)들이 있다. 국내외에 이러한 플랫폼을 이용하여 데이터를 공유하거나, 분야별로 데이터 저장소들이 증가일로에 있다. 나아가, 최근 단순히 공유하는 것을 뛰어넘어 사용자들에게 데이터 분석을 용이하게 하는 분석 개발 서비스환경을 제공하는 시도가 MS, Google, AWS등에서 보이고 있다. 본 논문에서는 이러한 일련의 플랫폼 개발 동향 및 그들의 특징을 살펴보고, 현존하는 분석형 데이터 플랫폼이 지향하는 기능들에 대해 살펴보기로 한다.

• Database Research
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• v.34 no.3
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• pp.69-85
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• 2018

Many researches proposed federated query engines to perform query on several homogeneous or heterogeneous datasets simultaneously that significantly improve the quality of query results. The existing techniques allow querying only over a few heterogeneous datasets considering the static binding using the non-standard query. However, we observe that a simultaneous system considering the integration of heterogeneous metadata standards can offer better opportunity to generalize the query over any homogeneous and heterogeneous datasets. In this paper, we propose a transparent federated engine (DRAZ) to query over multiple data sources using SPARQL. In our system, we first develop the ontology for a non-RDF metadata standard based on the metadata kernel dictionary elements, which are standardized by the metadata provider. For a given SPARQL query, we translate any triple pattern into an API call to access the dataset of corresponding non-RDF metadata standard. We convert the results of every API call to N-triples and summarize the final results considering all triple patterns. We evaluated our proposed DRAZ using modified Fedbench benchmark queries over heterogeneous metadata standards, such as DCAT and DOI. We observed that DRAZ can achieve 70 to 100 percent correctness of the results despite the unavailability of the JOIN operations.